WO2023204622A1

WO2023204622A1 - Diagnostic aid device and method using smart hemodynamic indices

Info

Publication number: WO2023204622A1
Application number: PCT/KR2023/005368
Authority: WO
Inventors: 송시몬; 안돈관; 이상형; 김두상
Original assignee: 한양대학교 산학협력단; 서울대학교 산학협력단; 한국보훈복지의료공단
Priority date: 2022-04-21
Filing date: 2023-04-20
Publication date: 2023-10-26

Abstract

The present invention relates to a diagnostic aid device and method using smart hemodynamic indices and, more particularly, to a diagnostic aid device and method for aid in medical decision-making, by calculating smart hemodynamic indices, which is a combination of smart indices with hemodynamic indices, and providing diagnosis results according to quantitatively standardized clinical guidelines by using the smart hemodynamic indices.

Description

Diagnostic assistance device and method using smart hemodynamic indicators

The present invention relates to a diagnostic assistance device and method using a smart hemodynamic index. More specifically, the present invention relates to a diagnostic assistance device and method that uses a smart hemodynamic index to calculate a smart hemodynamic index that combines the smart index and the hemodynamic index, and to quantitatively standardize the smart hemodynamic index using the smart hemodynamic index. It concerns technology that assists medical decisions by providing diagnostic results according to clinical guidelines.

Fractional flow reserve (FFR) is a technique to diagnose the degree of progression of stenosis by measuring the pressure inside the blood vessel that is reduced due to coronary artery stenosis.

The method for calculating hemodynamic indicators according to the prior art uses only a single pressure indicator among hemodynamic factors, so there is a gray area in the standard and requires considerable time, cost, and professional manpower for measurement.

In other words, the hemodynamic index according to the prior art consumes a lot of cost and time to calculate, so it is wasteful in the judgment of diagnosis and prognosis prediction during the medical diagnosis process.

In addition, the method for calculating hemodynamic indices according to the prior art has a problem of low reliability because it may be inconsistent with the judgment of an actual clinician.

The present invention is a diagnostic assistance device that assists medical decisions by calculating a smart hemodynamic index that combines smart index and hemodynamic index and providing diagnostic results according to quantitatively standardized clinical guidelines using the smart hemodynamic index. The purpose is to provide a method.

The present invention is an innovative diagnostic technology that can quantitatively express the analysis process and results, which require a high level of understanding of both hemodynamics and medicine, in standardized numbers and present matching clinical guidelines, and integrates the hemodynamic indicators and smart indicators. By providing smart hemodynamic indicators, the goal is to innovatively simplify the existing medical diagnosis process and at the same time assist in accurate diagnosis and prognosis prediction through more diverse considerations.

The present invention uses information that can be obtained from existing medical devices to calculate formalized indicators such as smart indicators, hemodynamic indicators, and smart hemodynamic indicators that integrate them, so it does not require the purchase of new medical devices. 1, 2, The purpose is to provide diagnostic assistance devices and methods that can be used in all tertiary medical environments.

A diagnostic assistance device using a smart hemodynamic index according to an embodiment of the present invention includes a clinical information collection unit that collects clinical information related to the diagnosis target, a clinical factor calculation unit that calculates clinical factors based on the collected clinical information, A hemodynamic factor calculation unit that calculates hemodynamic factors based on the collected clinical information, calculates a smart index (SI) using the calculated clinical factors, and calculates blood flow using the calculated hemodynamic factors. An index calculation unit that calculates a hemodynamic index (HDI) and calculates a smart hemodynamic index (SHDI) by simultaneously considering the calculated smart index and the calculated hemodynamic index, and the calculated smart index It may include a diagnostic result provider that provides a diagnostic result for the diagnosis target by applying any one of the index, the calculated hemodynamic index, and the calculated smart hemodynamic index to a diagnostic guideline.

The index calculation unit may calculate a hemodynamic standard factor obtained by standardizing the hemodynamic factor, and calculate the hemodynamic index by assigning a weight to the calculated hemodynamic standard factor.

The indicator calculation unit may calculate a clinical standard factor obtained by standardizing the clinical factor, and calculate the smart indicator by assigning a weight to the calculated clinical standard factor.

The clinical factor calculation unit determines whether diabetes, blood pressure, hyperlipidemia, smoking, hematocrit, cholesterol level, pulse rate, ultrasound image, CT image, MRI image, pain, heart failure, etc. based on the characteristics of each disease in the clinical information. Clinical factors including at least one of body blood concentration, blood inflammation level, myocardial perfusion single-photon tomography image, underlying disease, hereditary condition, weight, and age can be calculated.

The diagnostic result provider provides clinical information related to the diagnostic target to a plurality of medical professionals, then applies a score based on any of the indicators to a diagnostic guideline determined based on the diagnosed results, and calculates the applied score from the diagnostic guideline. Diagnosis results corresponding to the score can be provided.

The clinical information collection unit collects medical images including at least one of angiography images, ultrasound Doppler images, and CT images according to clinical information acquisition standards, and applies an artificial intelligence prediction model to the collected medical images to create a three-dimensional space. And data on 4D blood flow information can be collected as clinical information.

The hemodynamic factor calculation unit includes at least one of a basic blood flow information factor, a velocity factor, a flow rate factor, a secondary flow factor, a wall stress-based factor, a pressure factor, and a morphology factor based on the 4-dimensional blood flow velocity information in the clinical information. Hemodynamic factors can be calculated.

The indicator calculation unit calculates a hemodynamic standard factor by assigning a score in a predefined score range according to the calculated hemodynamic factor, and classifies the disease into one of a plurality of diseases according to the calculated hemodynamic standard factor, , a hemodynamic index can be calculated by assigning a weight calculated according to the degree of the disease to the calculated hemodynamic standard factors.

The index calculation unit divides a plurality of cases in relation to the calculated hemodynamic factors, calculates a threshold value for each disease based on the average value of each of the divided cases, and calculates a threshold value for each disease based on the calculated threshold value. The hemodynamic standard factor can be calculated by assigning a score within the given score range.

The index calculation unit calculates a clinical standard factor by assigning a score in a predefined score range according to the calculated clinical factor, classifies the disease into one of a plurality of diseases according to the calculated clinical standard factor, and calculates the clinical factor. Smart indicators can be calculated by assigning weights calculated according to the degree of the disease to the clinical standard factors.

A diagnostic assistance method using a smart hemodynamic index according to an embodiment of the present invention includes the steps of collecting clinical information related to a diagnostic target in a clinical information collection unit, and calculating clinical factors from the collected clinical information in a clinical factor calculation unit. Calculating a hemodynamic factor in a hemodynamic factor calculation unit, calculating a hemodynamic factor from the collected clinical information, calculating a smart index (SI) using the calculated clinical factor in an index calculation unit, A hemodynamic index (HDI) is calculated using the calculated hemodynamic factor, and a smart hemodynamic index (SHDI) is calculated by simultaneously considering the calculated smart index and the calculated hemodynamic index. In the calculation step and the diagnosis result provision unit, any one of the calculated smart indicator, the calculated hemodynamic indicator, and the calculated smart hemodynamic indicator is applied to a diagnostic guideline to provide a diagnostic result for the diagnosis subject. It may include providing steps.

A smart index is calculated using the calculated clinical factors, a hemodynamic index is calculated using the calculated hemodynamic factors, and a smart hemodynamic index is calculated by simultaneously considering the calculated smart index and the calculated hemodynamic index. The calculating step includes calculating a hemodynamic standard factor obtained by standardizing the hemodynamic factor, calculating the hemodynamic index by assigning a weight to the calculated hemodynamic standard factor, and a clinical standard standardizing the clinical factor. It may include calculating a factor and assigning a weight to the calculated clinical standard factor to calculate the smart indicator.

The step of providing a diagnosis result for the diagnosis subject by applying any one of the calculated smart indicator, the calculated hemodynamic indicator, and the calculated smart hemodynamic indicator to a diagnostic guideline includes providing a diagnosis result for the diagnosis target to a plurality of professional medical professionals. After providing clinical information related to the diagnosis subject, applying a score based on one of the indicators to a diagnostic guideline determined based on the diagnosed result, providing a diagnostic result corresponding to the applied score in the diagnostic guideline. may include.

The step of collecting clinical information related to the diagnostic object includes collecting medical images including at least one of angiography images, ultrasound Doppler images, and CT images according to clinical information acquisition standards, and applying artificial intelligence to the collected medical images. It may include the step of applying a prediction model to collect data on 3D space and 4D blood flow information as clinical information.

The step of calculating the hemodynamic factor includes at least one of a basic blood flow information factor, a velocity factor, a flow rate factor, a secondary flow factor, a wall stress-based factor, a pressure factor, and a morphology factor based on the 4-dimensional blood flow velocity information in the clinical information. Comprising the step of calculating a hemodynamic factor including an abnormality, calculating a smart indicator using the calculated clinical factor, calculating a hemodynamic indicator using the calculated hemodynamic factor, and calculating the smart indicator In the step of calculating a smart hemodynamic index by integrating the hemodynamic index, a hemodynamic standard factor is calculated by assigning a score in a predefined score range according to the calculated hemodynamic factor, and the calculated hemodynamic standard Depending on the factors, the disease is classified into one of a plurality of diseases, and a hemodynamic index can be calculated by assigning a weight calculated according to the disease's degree to the calculated hemodynamic standard factors.

The step of calculating clinical factors based on the collected clinical information includes diabetes, blood pressure, hyperlipidemia, smoking, hematocrit, cholesterol level, pulse rate, ultrasound image, CT, based on the characteristics of each disease in the clinical information. Calculating clinical factors including at least one of the following: image, MRI image, pain, heart failure, body blood concentration, blood inflammation level, myocardial perfusion single-photon tomography image, underlying disease, hereditary condition, weight, and age. may include.

A smart index is calculated using the calculated clinical factors, a hemodynamic index is calculated using the calculated hemodynamic factors, and a smart hemodynamic index is calculated by simultaneously considering the calculated smart index and the calculated hemodynamic index. In the step of calculating, a clinical standard factor is calculated by assigning a score in a predefined score range according to the calculated clinical factor, and the disease is classified as one of a plurality of diseases according to the calculated clinical standard factor, It may include calculating a smart indicator by assigning weights calculated according to the disease to the calculated clinical standard factors.

The present invention is a diagnostic assistance device that assists medical decisions by calculating a smart hemodynamic index that combines smart index and hemodynamic index and providing diagnostic results according to quantitatively standardized clinical guidelines using the smart hemodynamic index. A method can be provided.

The present invention is an innovative diagnostic technology that can quantitatively express the analysis process and results, which require a high level of understanding of both hemodynamics and medicine, in standardized numbers and present matching clinical guidelines, and integrates the hemodynamic indicators and smart indicators. By providing smart hemodynamic indicators, the existing medical diagnosis process can be innovatively simplified and at the same time, it can assist in accurate diagnosis and prognosis prediction through more multifaceted consideration.

The present invention uses information that can be obtained from existing medical devices to calculate formalized indicators such as smart indicators, hemodynamic indicators, and smart hemodynamic indicators that integrate them, so it does not require the purchase of new medical devices. 1, 2, It can provide diagnostic assistance devices and methods that can be used in all tertiary care environments.

1 is a diagram illustrating a diagnostic assistance device using a smart hemodynamic index according to an embodiment of the present invention.

Figure 2 is a diagram illustrating a method for calculating a smart hemodynamic index according to an embodiment of the present invention.

Figure 3 is a diagram illustrating a method of improving the diagnostic process by applying a smart hemodynamic index according to an embodiment of the present invention.

Figure 4 is a diagram explaining hemodynamic factors according to an embodiment of the present invention.

Figure 5 is a diagram illustrating a configuration for standardizing hemodynamic factors according to an embodiment of the present invention.

Figure 6 is a diagram illustrating standardized clinical guidelines according to an embodiment of the present invention.

FIGS. 7A and 7B are diagrams illustrating a method of calculating weights of hemodynamic standard factors according to an embodiment of the present invention.

Figure 8 is a diagram illustrating a method of providing a current patient condition diagnosis result according to any one of a smart indicator, a hemodynamic indicator, and a smart hemodynamic indicator according to an embodiment of the present invention.

Figure 9 is a diagram for explaining a diagnostic assistance method using a smart hemodynamic index according to an embodiment of the present invention.

Hereinafter, various embodiments of this document are described with reference to the attached drawings.

The embodiments and terms used herein are not intended to limit the technology described in this document to a specific embodiment, and should be understood to include various changes, equivalents, and/or substitutes for the embodiments.

In the following description of various embodiments, if a detailed description of a related known function or configuration is judged to unnecessarily obscure the gist of the invention, the detailed description will be omitted.

The terms described below are terms defined in consideration of functions in various embodiments, and may vary depending on the intention or custom of the user or operator. Therefore, the definition should be made based on the contents throughout this specification.

In connection with the description of the drawings, similar reference numbers may be used for similar components.

Singular expressions may include plural expressions, unless the context clearly indicates otherwise.

In this document, expressions such as “A or B” or “at least one of A and/or B” may include all possible combinations of the items listed together.

Expressions such as “first,” “second,” “first,” or “second,” can modify the corresponding components regardless of order or importance and are used to distinguish one component from another. It is only used and does not limit the corresponding components.

When a component (e.g., a first) component is said to be "connected (functionally or communicatively)" or "connected" to another (e.g., second) component, it means that the component is connected to the other component. It may be connected directly to an element or may be connected through another component (e.g., a third component).

In this specification, “configured to” means “suitable for,” “having the ability to,” or “changed to,” depending on the situation, for example, in terms of hardware or software. ," can be used interchangeably with "made to," "capable of," or "designed to."

In some contexts, the expression “a device configured to” may mean that the device is “capable of” working with other devices or components.

For example, the phrase "processor configured (or set) to perform A, B, and C" refers to a processor dedicated to performing the operations (e.g., an embedded processor), or by executing one or more software programs stored on a memory device. , may refer to a general-purpose processor (e.g., CPU or application processor) capable of performing the corresponding operations.

Additionally, the term 'or' means 'inclusive or' rather than 'exclusive or'.

That is, unless otherwise stated or clear from the context, the expression 'x uses a or b' means any of the natural inclusive permutations.

In the above-described specific embodiments, components included in the invention are expressed in singular or plural numbers depending on the specific embodiment presented.

However, the singular or plural expressions are selected to suit the presented situation for convenience of explanation, and the above-described embodiments are not limited to singular or plural components, and even if the components expressed in plural are composed of singular or , Even components expressed as singular may be composed of plural elements.

Meanwhile, in the description of the invention, specific embodiments have been described, but of course, various modifications are possible without departing from the scope of the technical idea implied by the various embodiments.

Therefore, the scope of the present invention should not be limited to the described embodiments, but should be determined by the claims described below as well as equivalents to these claims.

Figure 1 illustrates the components of a diagnostic assistance device using a smart hemodynamic indicator according to an embodiment of the present invention.

Referring to FIG. 1, the diagnostic assistance device 100 using a smart hemodynamic index according to an embodiment of the present invention includes a clinical information collection unit 110, a clinical factor calculation unit 120, and a hemodynamic factor calculation unit 130. ), an indicator calculation unit 140, and a diagnosis result providing unit 150, and the control unit 160 controls the functional operation of the above-described configuration.

According to one embodiment of the present invention, the clinical information collection unit 110 collects clinical information related to the diagnosis subject.

Diagnosis targets are patients diagnosed with diseases related to hemodynamics and medicine. Representative diseases include carotid artery disease, and carotid artery disease includes carotid artery stenosis.

According to one embodiment of the present invention, the clinical information collection unit 110 may collect medical images including at least one of angiography images, ultrasound Doppler images, and CT images according to clinical information acquisition standards.

For example, the clinical information collection unit 110 may collect data on 3D space and 4D blood flow information as clinical information by applying an artificial intelligence prediction model to the collected medical images.

The clinical information includes the patient's 4-dimensional blood flow velocity information, and the blood flow velocity information is 3-dimensional space and 1 cardiac cycle obtained using methods such as 4D-flow-MRI and computational fluid dynamics (CFD). It can mean the three components of the velocity vector for the time information and the position information on the wall where the blood and blood vessels meet.

The data format of clinical information is basically input as a file in CSV (comma-separated values) format, but in some cases, it is input as a velocity vector 3-component (u, There is no special distinction between any data format that can record and read v, w).

According to one embodiment of the present invention, the clinical factor calculation unit 120 calculates clinical factors based on disease-specific characteristics of clinical information.

For example, clinical factors may be referred to as clinical parameters, such as diabetes, blood pressure, hyperlipidemia, smoking, hematocrit, cholesterol level, pulse rate, ultrasound image, CT image, MRI image, pain, heart failure, It may include at least one of the following: body blood concentration, blood inflammation level, myocardial perfusion single-photon tomography image, underlying disease, hereditary condition, weight, and age.

For example, the clinical factor calculation unit 120 determines whether diabetes, blood pressure, hyperlipidemia, smoking status, hematocrit, cholesterol level, pulse rate, ultrasound image, CT image, MRI image, pain, based on the characteristics of each disease in the clinical information. Clinical factors can be calculated, including at least one of the following: heart failure, body blood concentration, blood inflammation level, myocardial perfusion single-photon tomography image, underlying disease, hereditary disease, weight, and age.

According to one embodiment of the present invention, the hemodynamic factor calculation unit 130 calculates the hemodynamic factor based on 4D blood flow velocity information in clinical information.

For example, hemodynamic factors may be referred to as hemodynamic parameters.

The hemodynamic factor is calculated based on dimensionless 4-dimensional blood flow velocity information, and includes at least one of the basic blood flow information factor, velocity factor, flow rate factor, secondary flow factor, wall stress-based factor, pressure factor, and morphology factor. may include.

For example, the hemodynamic factor calculation unit 130 calculates basic blood flow information factors, velocity factors, flow rate factors, secondary flow factors, wall stress-based factors, pressure factors, and morphology based on dimensionless 4-dimensional blood flow velocity information. A hemodynamic factor including at least one of the factors can be calculated.

According to one embodiment of the present invention, the hemodynamic factor calculation unit 130 calculates the hemodynamic factor from blood flow velocity information, and the calculated hemodynamic factor can be summarized as in Table 1 below.

[Table 1]

According to one embodiment of the present invention, the hemodynamic factor calculation unit 130 may mathematically calculate the remaining parameters, excluding basic blood flow information and morphology parameters, from the velocity vector.

In this process, the parameter values can be used as is, or after going through a non-dimensionalization process, as calculated values for the parameters disclosed in Table 1.

A supplementary explanation will be given regarding hemodynamic factors or parameters using FIG. 4 .

For example, the index calculation unit 140 may calculate a hemodynamic standard factor obtained by standardizing the hemodynamic factor, and calculate the hemodynamic index by assigning a weight to the calculated hemodynamic standard factor.

According to one embodiment of the present invention, the indicator calculation unit 140 may calculate a clinical standard factor by standardizing clinical factors, and calculate a smart indicator by assigning a weight to the calculated clinical standard factor.

According to one embodiment of the present invention, the index calculation unit 140 calculates a smart index using the calculated clinical factors, calculates a hemodynamic index using the calculated hemodynamic factors, and combines the smart index and the hemodynamic index. By considering it simultaneously, smart hemodynamic indicators can be calculated.

The smart hemodynamic indicator is an indicator that is constructed by simultaneously considering the smart indicator and the hemodynamic indicator.

Therefore, the smart hemodynamic index may have different weights or formulas for score distribution (standard factors) for the factors used in the existing smart index and the hemodynamic index.

For example, the index calculation unit 140 calculates a hemodynamic standard factor by assigning a score in a predefined score range according to the hemodynamic factor, and determines which one of a plurality of diseases is determined according to the calculated hemodynamic standard factor. The hemodynamic index can be calculated by assigning weights calculated according to simple linear regression according to the degree of the disease to the calculated hemodynamic standard factors.

According to one embodiment of the present invention, the index calculation unit 140 divides a plurality of cases in relation to the calculated hemodynamic factors, calculates a threshold value for each disease based on the average value of each divided case, and calculates the calculated The hemodynamic standard factor can be calculated by assigning a score in a predefined score range based on the threshold.

For example, the indicator calculation unit 140 may assign a score to each hemodynamic parameter according to a predefined score range (0 to 10 points) according to the parameter value.

Using Figure 5, the standard hemodynamic factors related to hemodynamic factors are explained in supplementary form.

The indicator calculation unit 140 according to an embodiment of the present invention calculates a clinical standard factor by assigning a score in a predefined score range according to the calculated clinical factor, and determines which of a plurality of diseases is selected according to the calculated clinical standard factor. It is classified as a single disease, and a smart indicator can be calculated by assigning weights calculated according to simple linear regression according to the degree of the disease to the calculated clinical standard factors.

For example, the index calculation unit 140 can calculate a smart index using Equation 1 below, a hemodynamic index using Equation 2, and a smart hemodynamic index using Equation 3. there is.

[Equation 1]

In Equation 1, SI may represent a smart index, p _i may represent the value of a clinical factor, s _i may represent a clinical standard factor, and w _i may represent a weight.

[Equation 2]

In Equation 2, HDI may represent the hemodynamic index, p _i may represent the value of the hemodynamic factor, h _i may represent the hemodynamic standard factor, and w _i may represent the weight.

[Equation 3]

In Equation 3, SHDI may represent a smart hemodynamic index, f may represent an integration function, SI may represent a smart index, and HDI may represent a hemodynamic index.

Hemodynamic indices include existing hemodynamic factors such as Fractional Flow Reserve (FFR), Coronary Flow Reserve (CFR), Index of Microcirculatory Resistance (IMR), Wall Shear Stress (WSS), and Oscillatory Shear Index (OSI). It may be an indicator designed by normalizing and quantitatively formulating it through a weighted-sum model and population study to better reflect the characteristics of each cardiovascular region and disease.

Hemodynamic indicators can provide clear clinical guidelines for diagnosis and prognosis prediction for patients according to hemodynamic indicator values through large-scale clinical research.

Smart Index relates clinical information such as CT angiography currently used by clinicians to diagnose cardiovascular disease, presence of other diseases such as diabetes or high blood pressure, and blood components such as hematocrit or cholesterol level to each cardiovascular disease. It is designed as an integrated indicator by performing risk stratification by quantitatively evaluating it according to the degree, and is designed to have a high degree of consistency with existing medical decisions, so it can become a quantitative guideline.

The parameters in Table 1 can be configured to give them physical meaning using non-dimensionalization.

The non-dimensionalized equation can be exemplified as Equation 4 and Equation 5.

[Equation 4]

In Equation 4, h ₁ may represent a hemodynamic score based on a scoring equation defined for each parameter for non-dimensionalized hemodynamic parameters.

[Equation 5]

In Equation 5, h ₂ may represent a hemodynamic score based on a scoring equation defined for each parameter for non-dimensionalized hemodynamic parameters.

Smart Hemodynamic index is a single index that considers both hemodynamic index and smart index simultaneously.

The method of configuring smart indicators and smart hemodynamic indicators may be similar to hemodynamic indicators.

According to one embodiment of the present invention, the diagnostic result providing unit 150 may provide a diagnostic result for the diagnosis target by applying any one of the calculated hemodynamic index and the calculated smart hemodynamic index to the diagnostic guideline. there is.

For example, the diagnostic result provision unit provides clinical information related to the diagnosis target to a plurality of medical professionals and then applies a score based on any one indicator to the diagnostic guideline determined based on the diagnosed result to determine the applied score from the diagnostic guideline. Diagnosis results corresponding to the score can be provided.

For example, the diagnosis result provided by the diagnosis result provider 150 may be used as diagnostic assistance information for diagnosing a patient's disease, disease, etc.

Unlike the prior art myocardial fractional blood flow reserve, the smart hemodynamic index of the present invention is calculated by complexly considering a large variety of hemodynamic and clinical factors, so the quantitative judgment criteria can be relatively clear with no or small gray areas. Therefore, smart hemodynamic indicators have a high probability of matching actual clinical judgment.

In addition, diagnosis based on hemodynamic factors in the prior art requires a high level of expert knowledge in fluid mechanics, and when used clinically, there is a disadvantage of having to go through a comprehensive diagnosis/judgment process on clinical and epidemiological factors, whereas the present invention Smart hemodynamic indicators according to present simple and clear indicators, enabling quick decision-making during diagnosis.

In addition, since the smart hemodynamic index of the present invention is formulated using information obtained from existing medical devices and hemodynamic analysis methods, it does not require the purchase of new medical devices and can be used in all primary, secondary, and tertiary medical environments. It can be used in

In addition, as the incidence of cardiovascular disease continues to increase due to aging, and the burden of medical expenses increases accordingly, the utilization of smart hemodynamic indicators is expected to be very high.

However, the effects of the present invention are not limited to the effects described above, and may be expanded in various ways without departing from the spirit and scope of the present invention.

Therefore, the present invention is a diagnostic aid that calculates a smart hemodynamic index that combines smart index and hemodynamic index, and provides diagnostic results according to quantitatively standardized clinical guidelines using the smart hemodynamic index to assist medical decisions. Devices and methods can be provided.

Figure 2 illustrates a method for calculating a smart hemodynamic index according to an embodiment of the present invention.

Referring to FIG. 2, the method of calculating a smart hemodynamic index according to an embodiment of the present invention uses a clinical factor 200 and a hemodynamic factor 201 to calculate a smart index 210 and a hemodynamic index 211. , and illustrates a procedure for calculating the smart hemodynamic index 220 by simultaneously considering the calculated indices.

A method of calculating a smart hemodynamic index according to an embodiment of the present invention is a computerized simulation or real-time measurement technology (4-D) of the patient's 4D (time + 3D space) pulsatile vascular velocity field using angiography images and ultrasound Doppler. Flow MRI, 3D ultrasound, etc.) and clinical information obtained through artificial intelligence predictions learned from them.

The method for calculating a smart hemodynamic index according to an embodiment of the present invention includes various hemodynamic factors (FFR, CFR, IMR, WSS, OSI, etc.) and clinical factors (vascular stenosis rate, etc.) quantified using clinical information and velocity fields. Concomitant diseases, blood flow components, etc.) are calculated.

The method of calculating the smart hemodynamic index is to calculate the smart index (210) and the hemodynamic index (211) through standardization and formulation to suit the characteristics of each cardiovascular disease, and to calculate the smart hemodynamic index (220) by considering them simultaneously. Calculate

Figure 3 illustrates the effect of improving the diagnostic process by applying a smart hemodynamic indicator according to an embodiment of the present invention.

Referring to FIG. 3, steps S301 to S305 represent a diagnostic procedure according to the existing process, and steps S311 to S313 represent an improved diagnostic procedure according to the present invention.

According to the existing process, an anatomical evaluation of the lesion is made in step S301, a physiological evaluation of the lesion is made in step S302, a treatment method decision based on clinical information is made in step S303, and step (S303) is made. In S304), a decision is made regarding drug treatment and invasive treatment, and in step S305, periodic or regular follow-up management is performed.

The diagnostic assistance method according to an embodiment of the present invention is based on a smart hemo-dynamic index (SHDI) in step 311, and steps (S301) to (S303) according to the existing method during the diagnosis and management process. ) are integrated and simplified.

The diagnostic assistance method according to an embodiment of the present invention determines a SHDI-based treatment method in step S311, determines SHDI-based treatment timing in step S312, and performs SHDI-based tracking management in step S313. do.

Step (S301) takes about 10 hours to extract blood vessel shapes based on experts, step (S302) takes about 5 hours to present FFR based on computer simulation, and steps (S303) and (S304) require medical data dictionary The process of conducting clinical treatment after familiarization takes a long time.

Additionally, step S305 may correspond to prognostic management for ineffective periodic examinations and reoperations.

Meanwhile, step (S311) is AI-based automatic blood vessel shape extraction, which takes about 5 minutes, reducing manpower and time consumption, and improving fidelity and information usability through AI-based SHDI presentation.

Step (S312) improves clinical convenience and on-site response capabilities by accessing XR-based real-time medical data and performing procedures.

Step (S313) is SHDI-based prognosis prediction and establishment of a customized management plan to increase prognosis management efficiency and prevent emergency situations in advance.

In other words, the diagnostic assistance method according to an embodiment of the present invention improves the convenience of diagnosis and treatment subjects based on SHDI and assists the operator in faster judgment and treatment.

Figure 4 illustrates the carotid artery in relation to hemodynamic parameters according to one embodiment of the invention.

Referring to FIG. 4, the carotid artery 400 may be model data analyzed based on velocity information obtained using data obtained through 4D MRI.

Hemodynamic parameters related to the carotid artery 400 can be summarized as in the table below.

The carotid artery 400 represents hemodynamic parameters and the Internal Carotid Artery (ICA), External Carotid Artery (ECA), and Common Carotid Artery (CCA).

The hemodynamic parameters can be summarized as in Table 2 below. The hemodynamic parameters are denoted by k, and in relation to the dimension, they represent MLT (M: mass, L: length, T: time).

Dimensions can dimensionally represent information about mass, length, and time.

[Table 2]

Hemodynamic parameters can be calculated mathematically based on velocity information in the carotid artery 400.

[Equation 6]

In Equation 6, Π may represent a hemodynamic factor that represents a physical meaning as a result of non-dimensionalization, and k may represent the value before non-dimensionalization of the hemodynamic factor, and can be organized as shown in Table 3 below.

[Table 3]

Non-dimensionalized hemodynamic factors can represent physical meaning and can be used to calculate hemodynamic indices.

Regarding the carotid artery 400, it can be divided into pre-surgery (Pre), post-surgery (Post), and a normal case (Control), which is the opposite side of the blocked case.

The carotid artery 400 can create a shape of the carotid artery using a 3D printer from a patient's CT image, reproduce the actual pulsation of the patient, and then provide speed information.

Figure 5 illustrates the standard for assigning scores to hemodynamic factors and standardizing them to calculate hemodynamic standard factors according to an embodiment of the present invention.

Referring to FIG. 5, the graph 500 represents PRE, which represents a value corresponding to the average of the stenotic carotid artery immediately before surgery, CTRL, which represents the carotid artery opposite the operated carotid artery, and POST, which represents the dilated carotid artery immediately after surgery. Based on the average of , the threshold value 501 for distinguishing stenosis and the threshold value 502 for distinguishing hyperdilatation are indicated.

In relation to PRE, if it is above the threshold value (501) corresponding to 90%, it can be indicated as stenosis, and if it is above the threshold value (502) corresponding to 10% in relation to POST, it can be confirmed as overextension.

It is assumed that the pi (Π) value for each group follows a normal distribution to distinguish between stenosis and dilatation.

Most PRE carotid arteries are given high scores, and very few POST carotid arteries are given low scores.

In other words, based on the pi value and graph 500 shown in Table 3, a score can be assigned to classify the data into stenosis, normal, and hyperdilatation.

In other words, for non-dimensionalized hemodynamic factors, a hemodynamic standard factor in the range of 0 to 10 can be assigned using a scoring formula defined for each factor.

The score range can be flexibly changed according to the user's settings, and can be defined as in Equation 7 below in relation to the non-dimensionalized hemodynamic factor and Equation 5.

[Equation 7]

In Equation 7, HP ₁ may represent a hemodynamic standard factor, and h ₁ may represent a hemodynamic factor.

According to the scoring of the physical meaning given based on Equation 7, the closer to “0” the carotid artery is classified as at risk due to excessive expansion, the closer to “5” it is classified as a normal carotid artery, and the closer to “10” the carotid artery is classified as at risk due to severe expansion. The closer it is, the more likely it is to be a carotid artery at risk due to excessive stenosis.

Figure 6 illustrates standardized clinical guidelines according to an embodiment of the present invention.

Referring to FIG. 6, an image 600 represents an index score 601 and a standardized clinical guideline 602.

The index score 601 can be used to determine surgery, stent, or other medical decisions according to quantitatively standardized clinical guidelines 602 and provide diagnostic assistance information to be applied to the patient.

The image 600 quantitatively provides criteria for medical decisions as a clinical guideline 602 using smart indicators, hemodynamic indicators, and smart hemodynamic indicators.

Figure 7a illustrates the degree of stenosis as a standard for calculating the weight of the hemodynamic standard factor according to an embodiment of the present invention.

Referring to FIG. 7A, a graph 700 indicates the degree of stenosis, and stenosis is confirmed by the portion where the size of the blood vessel is maintained and the point at which it is blocked.

It is a point that decreases and then increases. The degree of stenosis can be confirmed by the point that goes up and then goes down (701). Since d2 is linearly distributed, the hemodynamic index and smart hemodynamic index are numbers and have no meaning, so there is no meaning to the number. It is important to assign a number, and the analysis results show what the status is.

Stenosis can be expressed as Equation 8 below.

[Equation 8]

In Equation 8, d ₂ represents the change in length at a point that decreases and increases, and d _s can represent a peak point that goes up and then goes down.

Figure 7b shows the results of linear regression analysis of the weights of hemodynamic standard factors according to an embodiment of the present invention.

Referring to FIG. 7B, graph 710 shows PRE, CTRL, and POST for ICA.

Graph 711 represents PRE, CTRL, and POST for CCA.

Graph 712 shows PRE, CTRL, and POST for ECA.

Graph 713 shows PRE, CTRL, and POST for all carotids.

Graph 714 represents PRE, CTRL, and POST for the combination of ICA and CCA.

PRE represents the average value of the stenotic carotid artery immediately before surgery, CTRL represents the carotid artery opposite the operated carotid artery, and POST can represent the dilated carotid artery immediately after surgery.

In graphs 710 to 714, R ² represents a linearly distributed indicator (numerical value).

Weights (w _i ) are assigned to the hemodynamic standard factors according to an embodiment of the present invention, and hemodynamic indicators and smart hemodynamic indicators can be calculated through a weighted-sum method.

The weights can be calculated by performing a simple linear regression analysis on the hemodynamic standard factors and stenosis for a total of 24 carotid arteries, and the coefficient of determination (R_squarei) of the hemodynamic standard factors can be summarized as shown in Equation 9 below. That is, the weight can be calculated using Equation 9.

[Equation 9]

In Equation 9, w _i may represent a weight, and R_squre _i may represent the coefficient of determination of the weight.

In other words, a hemodynamic index can be calculated by combining weights with the hemodynamic standard factor calculated based on the hemodynamic factor.

Smart indicators can also be calculated in the same way as hemodynamic indicators.

Figure 8 illustrates a method of providing a current patient condition diagnosis result according to any one of a smart indicator, a hemodynamic indicator, and a smart hemodynamic indicator according to an embodiment of the present invention.

Referring to FIG. 8, the diagnostic assistance method according to an embodiment of the present invention can provide diagnostic results according to the values of the smart index, hemodynamic index, and smart hemodynamic index and clinical diagnosis guidelines.

For example, the clinical diagnosis guideline 800 may include scores and guide information determined by a plurality of professional medical professionals based on clinical information related to the diagnosis subject.

For example, the clinical diagnosis guideline can be presented as Table 4 below, and the table below illustrates the clinical diagnosis guideline according to the hemodynamic index as an indicator, but is equally applicable to smart indicators and smart hemodynamic indicators. Some figures may be subject to change.

[Table 4]

For example, the clinical diagnosis guideline 800 presents all of the patient's comprehensive medical information to multiple specialists, and links the results of carotid artery diagnosis with index values.

Therefore, the present invention does not require the purchase of new medical devices because it calculates smart indicators, hemodynamic indicators, and smart hemodynamic indicators that integrate them, which are formalized indicators using information that can be obtained from existing medical devices. It can provide diagnostic assistance devices and methods that can be used in both secondary and tertiary medical environments.

Figure 9 illustrates a diagnostic assistance method using a smart hemodynamic indicator according to an embodiment of the present invention.

Referring to FIG. 9, in step S901, the diagnostic assistance method using a smart hemodynamic indicator according to an embodiment of the present invention collects clinical information.

That is, the diagnostic assistance method using a smart hemodynamic index according to an embodiment of the present invention collects clinical information related to the diagnosis subject.

For example, clinical information collects medical images including at least one of angiography images, ultrasound Doppler images, and CT images according to clinical information acquisition standards, and applies an artificial intelligence prediction model to the collected medical images to provide three-dimensional Data on spatial and 4-dimensional blood flow information can be collected as clinical information.

In step S902, the diagnostic assistance method using a smart hemodynamic index according to an embodiment of the present invention calculates clinical factors.

In other words, the diagnostic assistance method using a smart hemodynamic index according to an embodiment of the present invention can calculate clinical factors based on the characteristics of each disease from the collected clinical information.

In step S903, the diagnostic assistance method using a smart hemodynamic indicator according to an embodiment of the present invention calculates a hemodynamic factor.

That is, the diagnostic assistance method using a smart hemodynamic index according to an embodiment of the present invention can calculate hemodynamic factors based on 4D blood flow velocity information.

For example, hemodynamic factors may be referred to as hemodynamic parameters.

Hemodynamic factors are calculated based on dimensionless 4-dimensional blood flow velocity information from clinical information, and include basic blood flow information factors, velocity factors, flow factors, secondary flow factors, wall stress-based factors, pressure factors, and morphology factors. It may contain at least one or more.

In step S904, the diagnostic assistance method using a smart hemodynamic index according to an embodiment of the present invention calculates a smart index, a hemodynamic index, and a smart hemodynamic index.

That is, the diagnostic assistance method using a smart hemodynamic index according to an embodiment of the present invention calculates a smart index using clinical factors, calculates a hemodynamic index using hemodynamic factors, and calculates the smart index and hemodynamic index. Smart hemodynamic indicators can be calculated by simultaneously considering.

In step S905, the diagnostic assistance method using a smart hemodynamic index according to an embodiment of the present invention provides a diagnosis result by applying the smart hemodynamic index to a diagnostic guideline.

In other words, the diagnostic assistance method using a smart hemodynamic index according to an embodiment of the present invention can provide diagnostic results for a diagnosis target by applying any one of the hemodynamic index and the smart hemodynamic index to the diagnostic guideline. there is.

In addition, the diagnostic assistance method using a smart hemodynamic indicator according to an embodiment of the present invention provides clinical information related to the diagnostic target to a plurality of professional medical professionals and then follows the diagnostic guideline determined based on the diagnostic results. By applying scores based on indicators, it is possible to provide diagnostic results corresponding to the scores applied in the diagnostic guidelines.

Therefore, the present invention provides hemodynamic indicators and smart indicators, which are innovative diagnostic technologies that can quantitatively express analysis processes and results that require a high level of understanding of both hemodynamics and medicine in standardized numbers and present matching clinical guidelines. By providing integrated smart hemodynamic indicators, the existing medical diagnosis process can be innovatively simplified and at the same time, it can assist in accurate diagnosis and prognosis prediction through more multifaceted consideration.

The device described above may be implemented with hardware components, software components, and/or a combination of hardware components and software components. For example, devices and components described in embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA), It may be implemented using one or more general-purpose or special-purpose computers, such as a programmable logic unit (PLU), microprocessor, or any other device capable of executing and responding to instructions. A processing device may execute an operating system (OS) and one or more software applications that run on the operating system. Additionally, a processing device may access, store, manipulate, process, and generate data in response to the execution of software. For ease of understanding, a single processing device may be described as being used; however, those skilled in the art will understand that a processing device includes multiple processing elements and/or multiple types of processing elements. It can be seen that it may include. For example, a processing device may include a plurality of processors or one processor and one controller. Additionally, other processing configurations, such as parallel processors, are possible.

Software may include a computer program, code, instructions, or a combination of one or more of these, which may configure a processing unit to operate as desired, or may be processed independently or collectively. You can command the device. Software and/or data may be used on any type of machine, component, physical device, virtual equipment, computer storage medium or device to be interpreted by or to provide instructions or data to a processing device. , or may be permanently or temporarily embodied in a transmitted signal wave. Software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

Although the embodiments have been described with limited drawings as described above, various modifications and variations can be made by those skilled in the art from the above description. For example, the described techniques are performed in a different order than the described method, and/or components of the described system, structure, device, circuit, etc. are combined or combined in a different form than the described method, or other components are used. Alternatively, appropriate results may be achieved even if substituted or substituted by an equivalent.

Therefore, other implementations, other embodiments, and equivalents of the claims also fall within the scope of the claims described below.

Claims

A clinical information collection unit that collects clinical information related to the diagnosis subject;

a clinical factor calculation unit that calculates clinical factors based on the collected clinical information;

a hemodynamic factor calculation unit that calculates a hemodynamic factor based on the collected clinical information;

A smart index (SI) is calculated using the calculated clinical factors, a hemodynamic index (HDI) is calculated using the calculated hemodynamic factors, and the calculated smart index and the calculated an index calculation unit that calculates a smart hemodynamic index (SHDI) by simultaneously considering the hemodynamic index; and

and a diagnostic result providing unit that provides a diagnostic result for the diagnosis target by applying any one of the calculated smart index, the calculated hemodynamic index, and the calculated smart hemodynamic index to a diagnostic guideline. to do

Diagnostic assistance device using smart hemodynamic indicators.
According to paragraph 1,

The index calculation unit calculates a hemodynamic standard factor that standardizes the hemodynamic factor, and calculates the hemodynamic index by assigning a weight to the calculated hemodynamic standard factor.

Diagnostic assistance device using smart hemodynamic indicators.
According to paragraph 1,

The indicator calculation unit calculates a clinical standard factor that standardizes the clinical factor, and calculates the smart indicator by assigning a weight to the calculated clinical standard factor.

Diagnostic assistance device using smart hemodynamic indicators.
According to paragraph 1,

The clinical factor calculation unit determines whether diabetes, blood pressure, hyperlipidemia, smoking, hematocrit, cholesterol level, pulse rate, ultrasound image, CT image, MRI image, pain, heart failure, etc. based on the characteristics of each disease in the clinical information. Characterized by calculating clinical factors including at least one of body blood concentration, blood inflammation level, myocardial perfusion single-photon tomography image, underlying disease, hereditary condition, body weight, and age.

Diagnostic assistance device using smart hemodynamic indicators.
According to paragraph 1,

The diagnostic result provider provides clinical information related to the diagnostic target to a plurality of medical professionals, then applies a score based on any of the indicators to a diagnostic guideline determined based on the diagnosed results, and calculates the applied score from the diagnostic guideline. Characterized by providing diagnostic results corresponding to the score

Diagnostic assistance device using smart hemodynamic indicators.
According to paragraph 1,

The clinical information collection unit collects medical images including at least one of angiography images, ultrasound Doppler images, and CT images according to clinical information acquisition standards, and applies an artificial intelligence prediction model to the collected medical images to create a three-dimensional space. And characterized by collecting data on 4-dimensional blood flow information as clinical information.

Diagnostic assistance device using smart hemodynamic indicators.
According to paragraph 1,

The hemodynamic factor calculation unit includes at least one of a basic blood flow information factor, a velocity factor, a flow rate factor, a secondary flow factor, a wall stress-based factor, a pressure factor, and a morphology factor based on the 4-dimensional blood flow velocity information in the clinical information. Characterized by calculating hemodynamic factors

Diagnostic assistance device using smart hemodynamic indicators.
In clause 7,

The index calculation unit calculates a hemodynamic standard factor by assigning a score in a predefined score range according to the calculated hemodynamic factor, and classifies the disease into one of a plurality of diseases according to the calculated hemodynamic standard factor, , Characterized in calculating the hemodynamic index by assigning a weight calculated according to the degree of the disease to the calculated hemodynamic standard factors.

Diagnostic assistance device using smart hemodynamic indicators.
According to clause 8,

The index calculation unit divides a plurality of cases in relation to the calculated hemodynamic factors, calculates a threshold value for each disease based on the average value of each of the divided cases, and calculates a threshold value for each disease based on the calculated threshold value. Characterized by calculating the hemodynamic standard factor by assigning a score in the given score range.

Diagnostic assistance device using smart hemodynamic indicators.
According to paragraph 1,

The index calculation unit calculates a clinical standard factor by assigning a score in a predefined score range according to the calculated clinical factor, classifies the disease into one of a plurality of diseases according to the calculated clinical standard factor, and calculates the clinical factor. Characterized by calculating a smart indicator by assigning weights calculated according to the degree of the disease to clinical standard factors.

Diagnostic assistance device using smart hemodynamic indicators.
In a clinical information collection unit, collecting clinical information related to a diagnosis object;

In a clinical factor calculation unit, calculating clinical factors from the collected clinical information;

In a hemodynamic factor calculation unit, calculating a hemodynamic factor from the collected clinical information;

In the index calculation unit, a smart index (SI) is calculated using the calculated clinical factors, a hemodynamic index (HDI) is calculated using the calculated hemodynamic factors, and the calculated Calculating a smart hemodynamic index (SHDI) configured by considering the smart index and the calculated hemodynamic index; and

In the diagnosis result providing unit, applying any one of the calculated smart indicator, the calculated hemodynamic indicator, and the calculated smart hemodynamic indicator to a diagnostic guideline to provide a diagnostic result for the diagnosis target. Characterized by including

Diagnostic assistance method using smart hemodynamic indicators.
According to clause 11,

A smart index is calculated using the calculated clinical factors, a hemodynamic index is calculated using the calculated hemodynamic factors, and a smart hemodynamic index is calculated by simultaneously considering the calculated smart index and the calculated hemodynamic index. The step of calculating is,

Calculating a hemodynamic standard factor obtained by standardizing the hemodynamic factor, and calculating the hemodynamic index by assigning a weight to the calculated hemodynamic standard factor; and

Calculating a clinical standard factor that standardizes the clinical factor, and calculating the smart indicator by assigning a weight to the calculated clinical standard factor.

Diagnostic assistance method using smart hemodynamic indicators.
According to clause 11,

The step of providing a diagnosis result for the diagnosis subject by applying any one of the calculated smart indicator, the calculated hemodynamic indicator, and the calculated smart hemodynamic indicator to a diagnostic guideline,

After providing clinical information related to the diagnosis subject to a plurality of professional medical professionals, a score based on any of the above indicators is applied to a diagnostic guideline determined based on the diagnosed results, and a diagnosis corresponding to the applied score in the diagnostic guideline is made. Characterized by comprising the step of providing a result

Diagnostic assistance method using smart hemodynamic indicators.
According to clause 11,

The step of collecting clinical information related to the diagnostic target is,

Collect medical images including at least one of angiography images, ultrasound Doppler images, and CT images according to clinical information acquisition standards, and apply an artificial intelligence prediction model to the collected medical images to determine three-dimensional space and four-dimensional blood flow flow. Characterized by comprising the step of collecting data about information as clinical information

Diagnostic assistance method using smart hemodynamic indicators.
According to clause 11,

The step of calculating the hemodynamic factor is,

Calculating a hemodynamic factor including at least one of a basic blood flow information factor, a velocity factor, a flow rate factor, a secondary flow factor, a wall stress-based factor, a pressure factor, and a morphology factor based on the 4-dimensional blood flow velocity information from the clinical information. Includes steps,

A smart index is calculated using the calculated clinical factors, a hemodynamic index is calculated using the calculated hemodynamic factors, and a smart hemodynamic index is calculated by simultaneously considering the calculated smart index and the calculated hemodynamic index. The step of calculating is,

A hemodynamic standard factor is calculated by assigning a score in a predefined score range according to the calculated hemodynamic factor, and classified into one of a plurality of diseases according to the calculated hemodynamic standard factor. Characterized by calculating a hemodynamic index by assigning weights calculated according to the degree of disease to the hemodynamic standard factors.

Diagnostic assistance method using smart hemodynamic indicators.
According to clause 11,

The step of calculating clinical factors based on the collected clinical information is,

From the above clinical information, based on the characteristics of each disease, whether diabetes, blood pressure, hyperlipidemia, smoking status, hematocrit, cholesterol level, pulse rate, ultrasound image, CT image, MRI image, pain, heart failure, body blood concentration, blood Comprising a step of calculating clinical factors including at least one of inflammation level, myocardial perfusion single-photon tomography image, presence of underlying disease, presence of hereditary disease, body weight, and age;

A smart index is calculated using the calculated clinical factors, a hemodynamic index is calculated using the calculated hemodynamic factors, and a smart hemodynamic index is calculated by simultaneously considering the calculated smart index and the calculated hemodynamic index. The step of calculating is,

A clinical standard factor is calculated by assigning a score in a predefined score range according to the calculated clinical factor, and classified into one of a plurality of diseases according to the calculated clinical standard factor, and the calculated clinical standard factor Characterized by including the step of calculating a smart indicator by assigning a weight calculated according to the degree of the disease.

Diagnostic assistance method using smart hemodynamic indicators.